R Notebook

library(tidyverse)
library(plotly)

levels_df <- read_csv("levels-cleaned.csv")

companyCompensation <- 
  levels_df %>%
  group_by(year, company) %>%
  summarise(yearly_compensation = mean(totalyearlycompensation))

cityCompensation <- 
  levels_df %>%
  group_by(year, location) %>%
  summarise(yearly_compensation = mean(totalyearlycompensation))

Yearly mean compensation for top 5 companies in 2017, 2018, 2019, 2020, 2021

companyCompensation2017 <- 
  companyCompensation %>%
  filter(year == 2017) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2018 <- 
  companyCompensation %>%
  filter(year == 2018) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2019 <- 
  companyCompensation %>%
  filter(year == 2019) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2020 <- 
  companyCompensation %>%
  filter(year == 2020) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2021 <- 
  companyCompensation %>%
  filter(year == 2021) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

subplot(companyCompensation2017, companyCompensation2018, companyCompensation2019, companyCompensation2020, companyCompensation2021, nrows = 5)

Yearly mean compensation for top 5 cities in 2017, 2018, 2019, 2020, 2021

cityCompensation2017 <- 
  cityCompensation %>%
  filter(year == 2017) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2018 <- 
  cityCompensation %>%
  filter(year == 2018) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2019 <- 
  cityCompensation %>%
  filter(year == 2019) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2020 <- 
  cityCompensation %>%
  filter(year == 2020) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2021 <- 
  cityCompensation %>%
  filter(year == 2021) %>%
  arrange(desc(yearly_compensation)) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

subplot(cityCompensation2017, cityCompensation2018, cityCompensation2019, cityCompensation2020, cityCompensation2021, nrows = 5)

Yearly mean compensation for last 5 companies in 2017, 2018, 2019, 2020, 2021

companyCompensation2017 <- 
  companyCompensation %>%
  filter(year == 2017) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2018 <- 
  companyCompensation %>%
  filter(year == 2018) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2019 <- 
  companyCompensation %>%
  filter(year == 2019) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2020 <- 
  companyCompensation %>%
  filter(year == 2020) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

companyCompensation2021 <- 
  companyCompensation %>%
  filter(year == 2021) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~company,
    type = "bar",
    text = ~paste(company, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

subplot(companyCompensation2017, companyCompensation2018, companyCompensation2019, companyCompensation2020, companyCompensation2021, nrows = 5)

Yearly mean compensation for last 5 cities in 2017, 2018, 2019, 2020, 2021

cityCompensation2017 <- 
  cityCompensation %>%
  filter(year == 2017) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2018 <- 
  cityCompensation %>%
  filter(year == 2018) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2019 <- 
  cityCompensation %>%
  filter(year == 2019) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2020 <- 
  cityCompensation %>%
  filter(year == 2020) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

cityCompensation2021 <- 
  cityCompensation %>%
  filter(year == 2021) %>%
  arrange(yearly_compensation) %>%
  head(n = 5) %>%
  plot_ly(
    x = ~yearly_compensation,
    y = ~location,
    type = "bar",
    text = ~paste(location, ": $", round(yearly_compensation), sep = ""),
    hoverinfo = "text"
  ) %>%
  layout(showlegend = FALSE)

subplot(cityCompensation2017, cityCompensation2018, cityCompensation2019, cityCompensation2020, cityCompensation2021, nrows = 5)